Correct composition of dephased behavioural models

This research is supported by EPSRC grant EP/M014290/1.Scenarios of execution are commonly used to specify partial behaviour and interactions between different objects and components in a system. To avoid overall inconsistency in specifications, various automated methods have emerged in the literature to compose (behavioural) models. In recent work, we have shown how the theorem prover Isabelle can be combined with the constraint solver Z3 to efficiently detect inconsistencies in two or more behavioural models and, in their absence, generate the composition. Here, we extend our approach further and show how to generate the correct composition (as a set of valid traces) of dephased models. This work has been inspired by a problem from a medical domain where different care pathways (for chronic conditions) may be applied to the same patient with different starting points.Postprin

Automated conflict resolution between multiple clinical pathways:A technology report

Background The number of people in the UK with three or more long-term conditions continues to grow and the management of patients with co-morbidities is complex. In treating patients with multimorbidities, a fundamental problem is understanding and detecting points of conflict between different guidelines which to date has relied on individual clinicians collating disparate information. Objective We will develop a framework for modelling a diverse set of care pathways, and investigate how conflicts can be detected and resolved automatically. We will use this knowledge to develop a software tool for use by clinicians that can map guidelines, highlight root causes of conflict between these guidelines and suggest ways they might be resolved. Method Our work consists of three phases. First, we will accurately model clinical pathways for six of the most common chronic diseases; second, we will automatically identify and detect sources of conflict across the pathways and how they might be resolved. Third, we will present a case study to prove the validity of our approach using a team of clinicians to detect and resolve the conflicts in the treatment of a fictional patient with multiple common morbidities and compare their findings and recommendations with those derived automatically using our novel software. Discussion This paper describes the development of an important software-based method for identifying a conflict between clinical guidelines. Our findings will support clinicians treating patients with multimorbidity in both primary and secondary care settings

A framework for automated conflict detection and resolution in medical guidelines

This research is supported by the MRC-funded UK Research and Innovation grant MR/S003819/1 and by EPSRC grant EP/M014290/1.Common chronic conditions are routinely treated following standardised procedures known as clinical guidelines. For patients suffering from two or more chronic conditions, known as multimorbidity, several guidelines have to be applied simultaneously, which may lead to severe adverse effects when the combined recommendations and prescribed medications are inconsistent or incomplete. This paper presents an automated formal framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidities focusing on medications. The presented extended framework has a front-end which takes guidelines captured in a standard modelling language and returns the visualisation of the detected conflicts as well as suggested alternative treatments. Internally, the guidelines are transformed into formal models capturing the possible unfoldings of the guidelines. The back-end takes the formal models associated with multiple guidelines and checks their correctness with a theorem prover, and inherent inconsistencies with a constraint solver. Key to our approach is the use of an optimising constraint solver which enables us to search for the best solution that resolves/minimises conflicts according to medication efficacy and the degree of severity in case of harmful combinations, also taking into account their temporal overlapping. The approach is illustrated throughout with a real medical example.Publisher PDFPeer reviewe

CHEMORECEPTOR DYNAMICS AND SIGNALING: NMR MEASUREMENTS WITHIN FUNCTIONAL COMPLEXES

Bacteria employ remarkable membrane-bound nanoarrays to sense their environment and direct their swimming. Arrays consist of chemotaxis receptor trimers of dimers that are bridged at their membrane-distal tips by rings of two cytoplasmic proteins, a kinase CheA and a coupling protein CheW. It is widely accepted that ligand binding to the receptor causes a 2 Å piston motion of a helix that extends through the periplasmic and transmembrane domains. However, it is not clear how the signal propagates 200 Å further to control activity of the kinase bound at the tip of the receptor. Dynamic changes within the cytoplasmic domain of the receptor have been proposed to play a key role in signal transmission. To test these proposals, we applied solid-state NMR to study the structure and dynamics of the E coli Asp receptor cytoplasmic fragment (U-13C,15N-CF) in native-like arrays of functional complexes with CheA and CheW. To detect segments that experience motions on the millisecond time scale, we use a 15N{13C} REDOR filter to remove signals from rigid backbone carbons and retain signals from backbone carbons with ms-timescale dynamics. This experiment exhibits only 60-70% of the expected REDOR dephasing, suggesting that 40-30% of the backbone has ms-timescale mobility that averages the ~ 1000 Hz 13C15N dipolar couplings. A novel REDOR-filtered DARR experiment led us to identify MH2 (methylation helix 2) as the region with ms-timescale motion. INEPT spectra reveal dynamics on the ns or shorter timescale. The INEPT-detectable regions are identified through a combination of biochemical and NMR approaches, to establish that MH1 (methylation helix 1) is mobile on the ns timescale. Interestingly, the INEPT and REDOR studies indicate the methylation region has asymmetric mobility: MH1 has ns-timescale dynamics that increase in the kinase-off state, and MH2 has ms-timescale dynamics that decrease in the kinase-off state. Thus these NMR measurements of the dynamics of CF within its functional complexes provide insight into the structural organization and signaling-related changes of the receptor methylation region, which is responsible both for transmitting the ligand-binding signal and for adaptation, both of which are critical to the chemotaxis response

Interacting quantum observables : categorical algebra and diagrammatics

This paper has two tightly intertwined aims: (i) to introduce an intuitive and universal graphical calculus for multi-qubit systems, the ZX-calculus, which greatly simplifies derivations in the area of quantum computation and information. (ii) To axiomatize complementarity of quantum observables within a general framework for physical theories in terms of dagger symmetric monoidal categories. We also axiomatize phase shifts within this framework. Using the well-studied canonical correspondence between graphical calculi and dagger symmetric monoidal categories, our results provide a purely graphical formalisation of complementarity for quantum observables. Each individual observable, represented by a commutative special dagger Frobenius algebra, gives rise to an Abelian group of phase shifts, which we call the phase group. We also identify a strong form of complementarity, satisfied by the Z- and X-spin observables, which yields a scaled variant of a bialgebra

An integrated approach to a combinatorial optimisation problem

Funding: MRC grant MR/S003819/1 and Health Data Research UK, an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities.We take inspiration from a problem from the healthcare domain, where patients with several chronic conditions follow different guidelines designed for the individual conditions, and where the aim is to find the best treatment plan for a patient that avoids adverse drug reactions, respects patient’s preferences and prioritises drug efficacy. Each chronic condition guideline can be abstractly described by a directed graph, where each node indicates a treatment step (e.g., a choice in medications or resources) and has a certain duration. The search for the best treatment path is seen as a combinatorial optimisation problem and we show how to select a path across the graphs constrained by a notion of resource compatibility. This notion takes into account interactions between any finite number of resources, and makes it possible to express non-monotonic interactions. Our formalisation also introduces a discrete temporal metric, so as to consider only simultaneous nodes in the optimisation process. We express the formal problem as an SMT problem and provide a correctness proof of the SMT code by exploiting the interplay between SMT solvers and the proof assistant Isabelle/HOL. The problem we consider combines aspects of optimal graph execution and resource allocation, showing how an SMT solver can be an alternative to other approaches which are well-researched in the corresponding domains.Postprin

Understanding market demand for agricultural products through consumer research: the coffee example

A theoretical model of coffee consumption in the U.K. is proposed, which is estimated and used to examine the influence of habit formation and advertising in the period 1957-80. This work challenges both the assumption of symmetrical consumer response and the statistical source for measuring coffee consumption. The model allows for asymmetrical consumer reactions. Explanatory variables are: price of coffee and of tea, income, advertising and the strength of the coffee drinking habit. This work is original in terms of interpreting and quantifying product field advertising and habit formation; and for allowing a minimal threshold level of predictors. Mistakes, repeated printing errors and unpublished changes in definitions were found in the statistics of domestic coffee supplies 0 Household coffee purchases estimated by the National Food Survey (N.F.S.) are consistently over-reported. Causes investigated provide grounds for correcting estimates by pooling N.F.S. with Family Expenditure Survey; the result is consistent with adjusted supplies. Advertising effect on demand is separated into two aspects. The first action increases sales by attracting new buyers, while protecting consumers from competitors' propaganda. The second action increases sales to habitual customers, while manufacturers are competing through advertising for a larger brand share. The transmission medium is a factor in both effects. The strength of the habit shifts market demand function. A routine way of thinking prevails under stationary conditions; yet shifts in the function occur in a non-stationary situation which initiates the problem-solving way of thinking. In the model, addiction can be either absolute or relative to changes in other factors. All the evidence supports the general model proposed, which shows that a non-symmetrical functional effect prevails and demonstrates the existence of an adjustment period. Irrefutably, coffee consumption depends on former consumption levels, coffee price, price-ratio tea to coffee, income and advertising

Brain Energy Metabolism in Chronic Hepatic Encephalopathy: an in vivo and longitudinal Magnetic Resonance Spectroscopy study on a rat model of Biliary Cirrhosis

Hepatic Encephalopathy is a major neuropsychiatric syndrome that arises from acute and chronic liver disease-induced cerebral disorders. Chronic hepatic encephalopathy is associated with cirrhosis and stems from progressive liver brosis, thereby inducing portal hypertension and deterioration in liver function. Hepatic encephalopathy is characterized by increased levels of ammonia, named hyperammonemia. Given that hepatic encephalopathy induces disturbances in cerebral osmoregulation, neurotransmission, antioxidant and energy metabolism, 1H magnetic resonance spectroscopy was performed longitudinally on a rat model of Type C chronic hepatic encephalopathy to assess cerebral osmolyte, energy, neurotransmitter and antioxidant metabolite concentrations. This technique was combined with 31P Magnetic resonance spectroscopy with the purpose of measuring additional energy metabolite concentrations. The studies were carried out at 9.4 Tesla. Rats undergone bile-duct ligation and studies were performed at several stages of disease progression: 0, 4, 6 and 8 weeks after surgery. Results regarding brain osmolyte concentration showed a signi cant increase in Gln, a decrease in tChol and Ins as well as trends of decrease in Tau and Cr. These results suggest an osmoregulatory response to the increase of Gln. In what concerns to neurotransmission, a decrease was observed in Asp and Glu suggesting that neurotransmission is a ected by hyperammonemia which may be an evidence of alterations in the out ow of Gln from astrocytes and interfere with Glu synthesis. The reduction of antioxidants Asc and GSH may indicate oxidative stress due to ammonia exposure. Small trends of decrease observed in -ATP and other energy metabolites which may be a sign of energy disturbances but not signi cant to cause brain oedema. Overall, an increase in concentration levels of Gln it is pointed as the main cause of the minimal brain oedema supported by Glutamine Hypothesis. The results of this study are encouraging and relevant for future studies

MRI Studies of Appetite Centre Function in Rodents

Many different regions of the brain are involved in appetite control. A full understanding of their function and interaction requires studying neuronal activity at high resolution simultaneously in space and time. Two Magnetic Resonance Imaging (MRI) methods can potentially achieve this goal. Manganese-Enhanced (MEMRI) uses the accumulation of administered Mn[2+], which is paramagnetic (hence MRI visible) and taken up by active neurons through voltage-gated Ca[2+] channels during action potentials. Haemodynamic methods use one or more of many MRI-visible changes that occur to circulating blood in a brain region when it changes activity. These include blood-oxygenation level dependent (BOLD) and cerebral blood volume weighted (CBV) MRI. The aim of this project was to further develop, adapt and then use these methods to study the effects on neuronal activity of stimuli related to appetite and energy balance. The majority of work went towards adapting MEMRI for this. Amongst many tested changes, improvements were made to the MRI acquisition protocol (specifically using fast spin echo rather than spin-echo acquisition) to make it more sensitive to Mn-induced signal changes, increase spatial coverage from partial to whole brain and rostro-caudal spatial resolution from 1 to 0.4mm, all while maintaining the same temporal resolution. Most importantly, the neuroimaging analysis framework used in haemodynamic functional MRI was adapted for use with MEMRI. This included the adaptation of spatial normalization software to handle Mn-sensitive T[1]-weighted images dominated by non-brain tissue rather than brain dominated T[2]/T*[2]-weighted images, and the generation of a signal change model for use in GLM. This enabled much more objective, reproducible and less laborious data analysis than with previous hand drawn ROIs. Attempts were made to use BOLD- and CBV-fMRI to study the effects of potent, appetite-modulating gut hormones on appetite, though these failed to produce a response